AI Ensemble Reads Soil Chemistry to Identify Crop Types With Record Accuracy
A new architecture-diverse TabNet ensemble classifies seven crop types from harmonized multi-source soil data with 90.5 percent accuracy, outperforming XGBoost ...
Tag: XGBoost
Machine learning maps Europe’s toxic metal emissions while keeping data leakage out
A leakage-controlled machine learning framework converts heterogeneous European emission products into metal-specific datasets, achieving high accuracy for cadmium, mercury, and ...
Machines and Maps Converge on the Drivers of Ghana’s Childhood Anemia Crisis
A hybrid multilevel and machine learning analysis of Ghana's 2022 Demographic and Health Survey identifies nine high-confidence predictors of childhood ...
AI Can Classify National CO2 Emission Levels, But Only If It Never Sees the Country Before
A new study tests whether trade, governance and environmental tax indicators can classify national CO2 emission levels, and finds that ...
Machine learning model forecasts respiratory disease activity despite hospital reporting delays
A sentinel hospital study in Guangzhou tested a reporting-lag-aware machine learning framework for seven-day-ahead forecasting of influenza, COVID-19 and Mycoplasma ...
AI Flags Hidden Self-Harm History in Europe’s Emergency Rooms
An interpretable machine learning model trained on European injury surveillance data can identify emergency department patients whose records show documented ...
Trust-Aware AI Framework Spots Oracle Manipulation in DeFi Before Prices Crash
Researchers at Vellore Institute of Technology have developed TOAD-ML, a machine learning framework that validates decentralized finance oracle price feeds ...
Machine Learning Meets Reality: Why Most Intraday Trading Strategies Die at the Broker’s Fee
A new study across 40 assets shows that after transaction costs, only a handful of machine learning intraday strategies remain ...
Federated learning brings privacy-first anomaly detection to smart grids
Smart grids promise a cleaner, more responsive electricity system, but they also carry a hidden vulnerability: every smart meter is ...
DepressNet: An Interpretable Machine Learning Framework for Stratifying Depression Severity From Psychometric Data
Researchers have built DepressNet, an interpretable stacking-ensemble machine learning framework that stratifies depression severity into five levels from DASS-42 questionnaire ...
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Mothers who receive childcare support from maternal grandparents show more parental warmth, finds NTU Singapore study
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University of Seville Breaks 120-Year-Old Mystery, Revises a Key Einstein Concept
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Bee body mass, pathogens and local climate influence heat tolerance
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Researchers record first-ever images and data of a shark experiencing a boat strike
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Groundbreaking Clinical Trial Reveals Lubiprostone Enhances Kidney Function
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